RightScale Blog - Google Compute Enginehttp://www.rightscale.com/blog/tag/google-compute-engine
enGoogle Compute Engine Live Migration Passes the Testhttp://www.rightscale.com/blog/cloud-industry-insights/google-compute-engine-live-migration-passes-test
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</div> <!-- /.easy_social_box --><div class="field field-name-body field-type-text-with-summary field-label-hidden"><div class="field-items"><div class="field-item even" property="content:encoded"> <p dir="ltr" style="line-height:1.15;margin-top:0pt;margin-bottom:0pt;"><strong><em>Update: March 26, 2014</em></strong></p><p dir="ltr" style="line-height:1.15;margin-top:0pt;margin-bottom:0pt;"><em>Google announced significant new price changes that will be very attractive to many cloud users. RightScale provides a detailed analysis of these price cuts in <a href="http://www.rightscale.com/blog/cloud-cost-analysis/google-slashes-cloud-prices-google-vs-aws-price-comparison" target="_blank">Google Slashes Cloud Prices: Google vs AWS Price Comparison</a>.</em></p><p dir="ltr" style="line-height:1.15;margin-top:0pt;margin-bottom:0pt;">&nbsp;</p><p>Last week Google announced the <a href="http://googlecloudplatform.blogspot.com/2013/12/google-compute-engine-is-now-generally-available.html" target="_blank">general availability</a>&nbsp;(GA)&nbsp;of its Google Compute Engine (GCE) cloud service. One of the more intriguing aspects of the GA release is described in this blurb from the Google Cloud Platform&nbsp;Blog:</p><p>“We’re introducing <a href="https://developers.google.com/compute/docs/zones#maintenance" target="_blank">transparent maintenance</a>&nbsp;that combines software and data center innovations with <a href="http://en.wikipedia.org/wiki/Live_migration" target="_blank">live migration</a> technology&nbsp;to perform proactive maintenance while your virtual machines keep running.”</p><p>What makes this concept of transparent maintenance&nbsp;noteworthy&nbsp;–&nbsp;and unique among cloud providers –&nbsp;is that it&nbsp;will allow Google to upgrade the hardware and the software (including security-related and other OS patches) of the physical infrastructure that GCE is running on without the interruption of the virtual machines that are running on that infrastructure. &nbsp;</p><p>When other cloud providers need to perform maintenance on their underlying hardware, you will typically receive&nbsp;an email a few days or weeks in advance letting you know that you need to shut down your instance and relaunch it within the provider’s cloud to have it reassigned to a different unaffected host. This is both a hassle for you as well as for your&nbsp;end users who experience downtime&nbsp;of the service provided by that instance. With live migration, the virtual machines are moved without any downtime or noticeable service degradation.</p><p><span style="font-size:16px;"><strong>What Our Test&nbsp;Revealed </strong></span></p><p>As a Google Cloud Platform Partner, RightScale gets&nbsp;a sneak peek at some of the new features and services that Google provides, so&nbsp;in addition to conducting a <a href="http://www.rightscale.com/blog/cloud-industry-insights/google-compute-engine-performance-test-rightscale-and-apica" target="_blank">GCE performance test&nbsp;</a>earlier this year,&nbsp;we were also able to test the new&nbsp;live migration feature a short while before the GA announcement. &nbsp;</p><p>We set up an environment that is fairly common among&nbsp;our customers. Our deployment had two load balancers running HAProxy on n1-standard-1 instances; an array of 10 PHP application servers, each running on an n1-standard-2 instance; and a MySQL master/slave pair, each running on an n1-standard-4 instance type. All these servers were in a single GCE zone with the exception of the slave database, which was running in a geographically disparate zone (we wanted to see if data replication was affected during the migration).</p><p>&nbsp;</p><p style="text-align: center;"><img alt="Google Compute Engine Live Migration Test Configuration" class="media-image" height="429" style="width: 717px; height: 429px;" width="717" typeof="foaf:Image" src="http://www.rightscale.com/blog/sites/default/files/GCE%20Diagram%202.png" /></p><p style="text-align: center;"><span style="font-size:12px;"><em>Google Compute Engine Live Migration Test Configuration</em></span></p><p>Normally we would not run all our load balancers and application servers in the same zone (thus creating a single point of failure), but for this test we wanted as much of our infrastructure as possible&nbsp;to be in the zone that was going to undergo the live migration. We ran an HTTP load testing utility against our deployment on an instance running in a cloud from another infrastructure-as-service (IaaS) provider, generating traffic across the public Internet with 20 concurrent connections with a random maximum delay of two seconds.</p><p>We ran this test for four hours with every request resulting in a write to the database in a very ordered way such that we could look for gaps in the data in a post-mortem analysis. &nbsp;</p><p>We kicked off our test, let the&nbsp;Google team&nbsp;know that we were ready, and then we waited to hear back from them that the migration was complete. A few hours later, we were told that our instances had actually been migrated twice – once off the hardware they were running on originally and then back to the hardware where they had started. &nbsp;</p><p>We took a look at our log files and all the data in the database and we saw…nothing unusual. In other words, if Google hadn’t told us that our instances had been migrated, we would have never known. All our logs and data looked normal, and we saw no changes in the RightScale Cloud Management dashboard to any of our resources, including the zone, instance sizes, and IP addresses.</p><p><span style="font-size:16px;"><strong>Repeatability and Consistency of Performance Prove Key </strong></span></p><p>This test validated that GCE live migration performs exactly as expected and that we can confidently recommend it to customers. I am not surprised that we achieved seamless live migration and no downtime to our applications during our test, because all of the GCE products and services that we have had early&nbsp;access to have performed flawlessly and,&nbsp;most importantly, consistently. With the repeatability and consistency of performance we have seen from Google, I believe&nbsp;the GCE platform to be&nbsp;an extremely reliable choice&nbsp;for enterprises on which to run&nbsp;all cloud-based workloads. With the recent announcement of <a href="http://www.rightscale.com/blog/cloud-industry-insights/google-gce-goes-ga-5-reasons-its-time-take-look" target="_blank">Google Compute Engine GA</a>&nbsp;and this new live migration capability, it’s now time to check out GCE.</p><p><em>To speak with a RightScale expert and learn how your enterprise can benefit from Google cloud management, <a href="http://www.rightscale.com/contact" target="_blank">contact us for a complimentary consultation</a>.</em></p> </div></div></div>Thu, 12 Dec 2013 17:32:36 +0000Brian Adler349 at http://www.rightscale.com/bloghttp://www.rightscale.com/blog/cloud-industry-insights/google-compute-engine-live-migration-passes-test#commentsGoogle GCE Goes GA: 5 Reasons It's Time to Take a Lookhttp://www.rightscale.com/blog/cloud-industry-insights/google-gce-goes-ga-5-reasons-its-time-take-look
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</div> <!-- /.easy_social_box --><div class="field field-name-body field-type-text-with-summary field-label-hidden"><div class="field-items"><div class="field-item even" property="content:encoded"> <p>Last night Google announced general availability of its Google Compute Engine (GCE) cloud service. Since GCE was first announced at Google IO in June 2012, cloud users and cloud pundits have been analyzing and theorizing about the significant impact Google could have in the IaaS market. While some may have questioned Google’s level of commitment to the initiative, all of its actions to date have highlighted that Google is indeed very serious about competing in IaaS.</p><p><img alt="Google Compute Engine" class="media-image" height="132" style="width: 125px; height: 87px; float: left; margin-left: 15px; margin-right: 15px;" width="190" typeof="foaf:Image" src="http://www.rightscale.com/blog/sites/default/files/styles/large/public/google-compute-engine_2.png?itok=MNUodBlz" />Cloud experts point out the strong technology foundation that Google is using to power its cloud services. Its flagship product, Google Search, is, by design, a highly compute-intensive workload that operates at massive scale and requires fast interconnects. It required a huge investment in infrastructure at a time well before cloud as we know it existed. Google also had the <a href="http://news.cnet.com/2100-1034_3-5537392.html" target="_blank">vision</a> to buy up dark fiber nearly ten years ago to create low-latency connections between its data centers. That investment helps power some of the most popular applications in the world — from Google Search to Maps to Apps. Now this same advanced infrastructure is available to GCE users. Anyone who has tried to distribute workloads across geographically separated regions knows how valuable it is to have access to a reliable, low-latency network connection available on demand.</p><p>Google has been focused on steadily moving GCE though the release lifecycle — going from Early Access to Public Availability in one year and now to General Availability (GA) just seven months later (as opposed to Gmail’s five-year beta phase). GCE is now generally available and with new key capabilities that make it ready to run enterprise workloads.</p><p>GCE’s public cloud entry alongside Amazon Web Services (AWS), Windows Azure, HP, IBM, and Rackspace will provide another cloud option to help accelerate adoption. Over the past year and a half, RightScale has worked with many customers deploying and evaluating GCE and we’ve consistently heard five reasons why they are interested in GCE as an IaaS option.</p><p><span style="font-size:16px;"><strong>1. Performance</strong></span></p><p>Based on RightScale tests, GCE exhibited extremely high performance with great flexibility. We ran load on GCE’s service and reported <a href="http://www.rightscale.com/blog/cloud-industry-insights/google-compute-engine-performance-test-rightscale-and-apica" target="_blank">detailed results in June</a> 2013 when we scaled a 3-tier app out to 42 servers with 200,000 concurrent users.</p><p>Google recently documented additional performance testing where it reached and sustained one million requests per second on GCE — not surprising considering that Google runs much of its own services on GCE. Complete architectural details and costs are outlined in this <a href="http://googlecloudplatform.blogspot.ca/2013/11/compute-engine-load-balancing-hits-1-million-requests-per-second.html" target="_blank">Google Cloud Platform blog post</a>.</p><p>RightScale customer Fishlabs is building its next gaming title, <em>Galaxy on Fire - Alliances</em>, on the GCE platform with the RightScale Multi-Cloud Platform. Fishlabs cites “performance and stability” as reasons for selecting GCE for its compute stack.</p><p><span style="font-size:16px;"><strong>2. Pricing</strong></span></p><p>Google offers very competitive pricing for GCE. From sub-hour billing to a <a href="https://developers.google.com/compute/pricing#machinetype" target="_blank">simple catalog</a> with linear scaling pricing, it’s very simple to make decisions on the basis of cost when you consider the performance you get for the price. For example, if you determine you need more horsepower on a particular application and decide to move from standard-2 infrastructure to standard-4 infrastructure, you may find that with GCE's incremental pricing, you'll be able to do more with the same spec instance compared to what other cloud providers offer. And if you run instances for 45 minutes instead of 60 minutes, you’ll pay proportional rates at the per-minute boundary. This can save you a lot of money when you run a workload that spans many instances and scales up and down regularly.</p><p>RightScale cloud cost management tools like <a href="https://www.rightscale.com/cloud-analytics-free-trial?campaign=70170000000jIPn&amp;utm_medium=blog" target="_blank">Cloud Analytics</a> and <a href="http://www.planforcloud.com/" target="_blank">PlanForCloud</a> can help you manage costs for GCE and other cloud providers across your cloud portfolio.</p><p><span style="font-size:16px;"><strong>3. Choice </strong></span></p><p>Most organizations today have a cloud portfolio strategy that leverages public and private cloud infrastructure from more than one provider. RightScale’s own research in 2013 found that <a href="http://www.rightscale.com/blog/cloud-industry-insights/rightscale-state-cloud-2013-new-industry-survey" target="_blank">77 percent of enterprises are planning to use more than one cloud provider</a>. Google’s GCE provides cloud users another option in the IT arsenal when it comes to running compute or memory intensive workloads that require low latency interconnects for distributing data. And if you already happen to be using Google services such as DoubleClick Ad Exchange, for example, you now have a viable, co-located IaaS option.</p><p style="padding: 0 40px;"><span style="font-size:20px;">"We’ve chosen to work with the Google Compute Engine and RightScale teams to meet our database scaling and repeatable deployment requirements across platforms. Using GCE and RightScale, our team had a fully functional deployment up and running in a week and we’re enthusiastic about measuring results and performance as we head from beta to launch."</span></p><p style="text-align: center;"><span style="font-size:16px;">Uli Sesselmann, IT Supervisor, Fishlabs</span></p><p><span style="font-size:16px;"><strong>4. Innovation</strong></span></p><p>Google has a longstanding reputation for innovating across a broad spectrum of technologies, and GCE is no exception. As one example, GCE has provided encryption of data at rest as a standard feature of its platform since its inception.</p><p>Another recent GCE innovation is the new transparent maintenance feature enabling automatic live migration of virtual machines to help customers stay up and running during planned data center maintenance windows. This live migration of VMs provides additional benefits by enabling automatic migration of virtual machines for host maintenance. GCE can automatically move your workloads once you’ve enabled the capability.</p><p>Lydia Leong, an analyst at Gartner, describes the <a href="http://cloudpundit.com/2013/11/14/google-compute-engine-and-live-migration/" target="_blank">benefit of live migration</a> in her blog: "It’s highly useful to have a technology that allows you to host maintenance without downtime for the instances, because this encourages you not to delay host maintenance (since you want to update the underlying host OS, hypervisor, etc.)."</p><p>Leong also <a href="http://cloudpundit.com/2013/11/15/infrastructure-resilience-fast-vm-restart-and-google-compute-engine/" target="_blank">points out that GCE has added an Automatic Restart capability</a> that helps increase resiliency in case of hardware failures: "This is one of the features that enterprises most want in an ‘enterprise-grade’ cloud IaaS offering. Now Google has it."</p><p>The combination of these two features means that properly architecting for high availability and disaster recovery has just become much easier.</p><p><span style="font-size:16px;"><strong>5. Enterprise Readiness </strong></span></p><p>With the announcement of GA, live migration, and automatic restart, along with earlier innovations around security and performance, GCE is now a serious contender for enterprise workloads. As IT organizations move through the <a href="http://www.rightscale.com/blog/cloud-industry-insights/cloud-computing-trends-2014-state-cloud-survey" target="_blank">stages of cloud maturity</a>, enterprises will select the most appropriate cloud infrastructure for each workload — and GCE has become a viable enterprise option.</p><p>In an upcoming blog post, we’ll share a deeper analysis of our hands-on testing of GCE live migrations.</p><p>To get started managing GCE with RightScale, sign up for a <a href="https://www.rightscale.com/free-trial?utm_source=Unified%20Free%20Trial&amp;utm_medium=blog&amp;utm_campaign=Google%20GCE%20Goes%20GA%3A%205%20Reasons%20It's%20Time%20to%20Take%20a%20Look" target="_blank">free trial of RightScale</a>.</p> </div></div></div>Tue, 03 Dec 2013 14:00:00 +0000Rishi Vaish347 at http://www.rightscale.com/bloghttp://www.rightscale.com/blog/cloud-industry-insights/google-gce-goes-ga-5-reasons-its-time-take-look#commentsGoogle Compute Engine Performance Test with RightScale and Apicahttp://www.rightscale.com/blog/cloud-industry-insights/google-compute-engine-performance-test-rightscale-and-apica
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</div> <!-- /.easy_social_box --><div class="field field-name-body field-type-text-with-summary field-label-hidden"><div class="field-items"><div class="field-item even" property="content:encoded"> <p>With the resources and flexibility cloud computing provides, any organization can run its applications in the world’s best data centers, on the world’s best networks and servers. Organizations looking to leverage cloud infrastructures want to understand how that translates to real-world application performance. We’ve seen growing interest in <a href="http://www.rightscale.com/products-and-services/multi-cloud-platform/google-cloud-management">Google Compute Engine</a> (GCE) among organizations considering a cloud strategy, so we teamed up with <a href="http://www.apicasystem.com" target="_blank">Apica</a>, a third-party website testing, optimization, and monitoring company, to test GCE to see what performance consumers of these resources can expect.</p><p>In our test, Apica drove traffic to a standard three-tier web application running on GCE. We used RightScale for <a href="http://www.rightscale.com/products-and-services/multi-cloud-platform/google-cloud-management" target="_blank">Google cloud management</a> to configure, monitor, and auto-scale the application deployment.</p><p>During the test, we scaled up to 330,000 page views per minute from 200,000 concurrent users, maxing out at 42 servers on GCE during the peak load. To put these numbers in perspective, <a href="http://blog.evernote.com/tech/2011/05/17/architectural-digest/" target="_blank">Evernote states</a> that its application on average receives 150M requests per day. Our testing on the GCE platform nearly doubles the load that Evernote typically experiences.</p><h3>Test Configuration</h3><p>The deployment configuration we used in this test was a typical three-tier web architecture consisting of a load-balancing tier, an application tier, and a database. We used WordPress as our test application, but the general architecture and process could apply to any web application.</p><p><img alt="" class="media-image" height="792" style="line-height: 1.538em; width: 800px; height: 518px;" width="1224" typeof="foaf:Image" src="http://www.rightscale.com/blog/sites/default/files/GCE-Load-Test-Architecture_0.png" /></p><p><strong style="line-height: 1.538em;">Load-Balancing Tier</strong></p><p>We deployed six load-balancing servers based on a RightScale pre-configured <a href="http://www.rightscale.com/library/server_templates/Load-Balancer-with-HAProxy-v13/lineage/9103" target="_blank">Load Balancer ServerTemplate</a>™, all running on GCE’s n1-standard-8-d machine type. We modified the ServerTemplate to bypass Apache on the load balancer, which can be a resource hog. As no SSL termination was required by our implementation, we handled external access via HAProxy directly.</p><p>With eight virtual cores at our disposal on these servers, we ran normal system operations on CPU-0, and tied seven HAProxy processes to CPU-1 through CPU-7 using the <span style="font-family: monospace;">nbproc</span> option to HAProxy. The load generated by the Apica test infrastructure was distributed to each of the six load-balancing servers using the standard <a href="http://en.wikipedia.org/wiki/DNS_round_robin" target="_blank">DNS round robin</a> <span style="line-height: 1.538em;">mechanism.</span></p><p><strong>Application Tier</strong></p><p>We implemented the application tier on servers based on the <a href="http://www.rightscale.com/library/server_templates/PHP-App-Server-v13-3-/lineage/2288" target="_blank">RightScale PHP App ServerTemplate</a> with modifications made to install the PHP-based WordPress application and the Alternative PHP Cache (APC) library for caching to improve performance. The application servers were GCE n1-standard-2-d machines configured in an auto-scaling array.</p><p>We configured a RightScale server array to start with a minimum of 15 application servers, a “grow by” value of 5, and a “shrink by” value of 1. In other words, each auto-scaling event in the up direction would add five application servers to the array, while a scale-down would remove one server. Our decision threshold was the standard 51 percent, which means that more than half of the servers had to agree on an action – grow or shrink – before that action would be initiated. Our calm time – the length of time in which votes would be ignored after a scale-up or scale-down event – was set to a very aggressive five minutes, which is outside our best practices (and was one of our lessons learned – more on that later).</p><p><strong>Database Tier</strong></p><p>We configured the database tier on a RightScale standard <a href="http://www.rightscale.com/library/server_templates/Database-Manager-for-MySQL-5-5/lineage/13699" target="_blank">MySQL 5.5 Database Manager ServerTemplate</a>. We used only a master database in this test, violating one of our best practices for database applications, but because this was not a production site, and because we did not have read/write splitting implemented on the application servers, it simplified our configuration and was sufficient for the needs of this variation of the test. The database server was running on an n1-standard-8-d machine type, similar to the load-balancing servers.</p><p>Rather than implement a caching tier, for this test we used only the caching provided by APC on each of the individual application servers.</p><h3>The Test Load</h3><p>Our performance partner, Apica, helped us design a real-world test with four load scenarios:</p><ol start="1"><li class="c3 c1">Browse the home page, select a random page, then select a random article</li><li class="c3 c1">Browse the home page, perform a search, load resulting article</li><li class="c1 c3">Browse the home page, open random article, post comment</li><li class="c3 c1">Browse the home page, log in to site, post article, log out</li></ol><p>We used weighted randomization to reflect realistic use characteristics of a high-traffic application – that is, the number of times users browsed pages (a read-only operation) was significantly higher than the number of times users posted comments, performed searches, or added new articles. We generated the load from 80 test servers located in eight different geographic regions of North America.</p><p>The test data consisted of 350 blog posts drawn from our own <span style="line-height: 1.538em;">RightScale Blog</span><span style="line-height: 1.538em;">, with static assets (JavaScript, CSS, and images), served from Google Cloud Storage, which we used as a content delivery network (CDN).</span></p><h3>The Test – and the Results</h3><p>Apica simulated more than 200,000 concurrent users during a testing period of one hour. We applied a ramp period of approximately 20 minutes to provide a realistic load introduction of the 200,000 concurrent users. During the test we were serving up to 330,000 page views per minute, and network throughput was approximately 2.3 Gbps, with 23,000 requests per second. We served more than 20 million page views using a maximum of 42 servers: 35 n1-standard-2-d machines in our application server array, six load balancers, and a database server. Over the course of the test we had four scale-up events, taking our array to its maximum of 35 app servers, and one scale-down event, reducing the application server count to 34 by the end of the test. Let’s take a graphical look at some of the key numbers.</p><p>In the figure below, we’ve used RightScale to zoom in on a portion of a single test and annotated it to indicate the timing of specific relevant events. You can see how each part of the process affected CPU utilization.</p><p><img alt="" class="media-image" height="460" style="line-height: 1.538em;" width="800" typeof="foaf:Image" src="http://www.rightscale.com/blog/sites/default/files/GCE-perf1_1.jpg" /><br><em>A single GCE performance test.</em></p><p>The figure below shows 24 hours of CPU utilization of CPU-0 on a typical load balancer. The spikes reflect multiple one-hour test runs. The majority of the CPU was spent in handling interrupts, which is to be expected given that thousands of requests were being sent to the load balancer every second, each of which required CPU cycles to handle the interrupt.</p><p><img alt="" class="media-image" height="312" style="line-height: 1.538em;" width="800" typeof="foaf:Image" src="http://www.rightscale.com/blog/sites/default/files/GCE-CPU0_1.jpg" /><br><em>GCE CPU-0 performance.</em></p><p>The next figure shows the CPU utilization of a non-zero CPU on the load balancer during the same 24-hour period, each of which was handling a single HAProxy process.</p><p><img alt="" class="media-image" height="314" style="line-height: 1.538em;" width="800" typeof="foaf:Image" src="http://www.rightscale.com/blog/sites/default/files/GCE-non-CPU0_0.jpg" /><br><em>GCE non-CPU-0 performance.</em></p><p>The graph below shows the interface traffic on a typical load balancer over 24 hours of testing. The majority of the packets were outbound, representing content being served to the clients, with the inbound packets comprising much smaller content requests.</p><p><img alt="" class="media-image" height="323" style="line-height: 1.538em;" width="800" typeof="foaf:Image" src="http://www.rightscale.com/blog/sites/default/files/GCE-network-traffic_0.jpg" /><br><em>GCE network traffic test results.</em></p><p>We did not pre-warm the cache (which you would almost certainly do in a production environment), so every page request to a new server resulted in a cache miss. At the beginning of the test, as well as at any time a new server was added, the application servers had to request each page from the database. They would then put the result of the query in their own cache so it would be available the next time it was requested, and then return the page to the client, which generated a short burst of network-related errors caused by the lack of cache on the application servers (though the error rate was extremely low – less than 0.1 percent) and a flurry of CPU activity. Once a new server had been running for a short while and had served many requests, its cache was then updated, and at this point the CPU utilization dropped and the errors ceased.</p><p>Similarly, every time a test user added a new post to the environment, the cache on all the application servers was invalidated, and there was a mad dash to the database by all the application servers to get up-to-date information. These cache invalidations caused CPU spikes on the application servers (as well as on the database server), which again resulted in a brief spurt of network errors.</p><p>Those results reaffirmed what we already knew – that a separate, distributed caching tier is a good thing. All of the errors we encountered can be attributed to cache misses on the individual application servers. With a separate caching tier, there would still be cache invalidation, but just one cache would be invalidated – the one on the separate tier. Each application server after the first one to make the request would find the new content in the cache without being responsible for retrieving and storing it itself. In addition, there would be only one request to the database for each new piece of content, instead of one per application server (up to 35 in our test). In future variations of this test, we plan to add this independent caching tier and compare our results.</p><h3>Possible Refinements</h3><p>We learned a few things that should help us improve our testing methodology for the next iteration of these tests. For instance, we chose to forgo a slave database, which is fine for a test bed or proof-of-concept, but would never be advisable for a production environment. As we were using the master database for all reads and writes, a slave would not have contributed in any meaningful way to the test we were executing. In future tests, if we made modifications to the load patterns to generate more database writes, and thus stress the database a bit more, we could use one or more slaves and do read/write splitting to improve our database performance. In the current test, the database was not stressed, so these additions were not necessary.</p><p>We also chose not to implement a separate, distributed caching tier. We expected the cache to be a problem (particularly on startup), and wanted to verify our assumptions, which were indeed confirmed. In future tests we plan to use a separate caching tier.</p><p>On the configuration side, we used a calm time with a very low value – just five minutes. As it turned out, this value was too low. It typically took about seven minutes for a server to become fully operational, so we had occasions where a second round of voting occurred before the servers that were launched as a result of the previous vote had a chance to enter the load balance pools.</p><p>So why did we choose five minutes? During our preliminary tests we found that a base GCE server booted in less than three minutes, but once we configured that server to install Apache, PHP, WordPress, the required plugins, the connection to the load balancer, and all the other necessary accoutrements, servers took about seven minutes before they began handling some of the workload. Our best practice is to set a calm time of “boot time of the server plus a little extra,” which we did not calculate correctly. As a result we ended up with extra servers in the mix until they were scaled down during the next voting cycle. This process had no negative impact on the application, but we incurred some minimal extra expense from the launch of unnecessary additional servers.</p><h3>Conclusion</h3><p>During our tests we created a massive load that simulated a real-world application experiencing a planned promotional push or viral-type event using a fairly vanilla configuration with very little tuning or tweaking. Through this process we showed that GCE, managed by RightScale, can help deploy, run, and manage intensely demanding applications on the cloud. Throughout the testing process, GCE exhibited extremely high performance, low complexity, and great flexibility. As a result, I am very excited about what GCE has to offer.</p><p>To see for yourself how RightScale can give your organization a powerful solution for Google cloud management, <a href="https://www.rightscale.com/free-trial?utm_source=Unified%20Free%20Trial&amp;utm_medium=blog&amp;utm_campaign=Google%20Compute%20Engine%20Performance%20Test%20with%20RightScale%20and%20Apica" target="_blank">sign up for a RightScale free trial</a>.</p><p><em>We extend a special thanks to <a href="http://apicasystem.com/" target="_blank">Apica</a> for the use of its tools and expertise in building our real-world load test. Apica provides proven technology for optimizing the performance of cloud and mobile applications, and offers cloud-based load testing and web performance monitoring tools to test applications for maximum capacity, daily performance, improved load times, and protection from peak loads.</em></p><p>&nbsp;</p> </div></div></div>Wed, 19 Jun 2013 15:31:14 +0000Brian Adler278 at http://www.rightscale.com/bloghttp://www.rightscale.com/blog/cloud-industry-insights/google-compute-engine-performance-test-rightscale-and-apica#commentsAn Introduction to the Google Cloud Platform from an Insiderhttp://www.rightscale.com/blog/cloud-industry-insights/introduction-google-cloud-platform-insider
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</div> <!-- /.easy_social_box --><div class="field field-name-body field-type-text-with-summary field-label-hidden"><div class="field-items"><div class="field-item even" property="content:encoded"> <p>At RightScale Compute last month, Evan Anderson, a technical lead on the Google Compute Engine (GCE) team, gave an introduction to the <a href="https://cloud.google.com/" target="_blank">Google Cloud Platform</a>, the company's flagship cloud computing offering, and talked about how the <a href="http://www.rightscale.com/products-and-services/multi-cloud-platform/google-cloud-management" target="_blank">RightScale cloud management platform complements GCE's functionality</a>.</p><p><!--more--></p><p>Anderson focused on two of the core components of Google Cloud Platform: Compute and Storage. The Compute component includes GCE, which is an IaaS platform, and App Engine, a platform for developing and hosting web applications. The Storage offering includes Cloud Storage and Cloud SQL.</p><p style="text-align:center;"><a href="/sites/default/files/2013/05/google-compute-engine1.jpg"><img alt="Google Compute Engine (GCE)" class="media-image size-full wp-image-2819 aligncenter" height="210" style="" width="280" typeof="foaf:Image" src="http://www.rightscale.com/blog/sites/default/files/styles/large/public/2013/05/google-compute-engine1.jpg?itok=Y7QRHJHL" /></a></p><p>GCE in particular is designed to run any application on Google's infrastructure. It offers scalable processing and storage and fast networking. While it's still officially in beta, Google itself uses GCE for dozens of projects internally. However, because it's in beta, Google schedules maintenance windows of up to two weeks every 20 weeks, one zone at a time. When you use the recommended multi-zone architecture, RightScale makes it easy to migrate your servers between zones when necessary.</p><p>Everything in GCE is built atop the same JSON REST API. You can access the API from a command-line tool called gcutil, several GUIs (including ones from both Google and RightScale), and libraries for 10 different languages.</p><p>The virtual machines that GCE uses offer one, two, four, or eight CPUs, and three available memory sizes: standard (3.75GB), highcpu (0.9GB), and highmem (6.5GB). Unlike Google App Engine, the VMs are not locked down - customers have root access to their VMs. Internet connectivity uses Google's fat pipes, with built-in firewalling. Every project (a project comprises VMs and their associated objects) gets its own private network with internal DNS naming so that you can use SSH to connect to named machines. After you have authenticated to Google once via SSH, you should never need to supply a password again to access a guest OS.</p><p>GCE offers three storage options. Persistent disk is triply replicated in the same zones that your virtual machines are in and remains in place even when the VMs themselves are not running. You can use local disk as scratch space. Finally, cloud storage is a blobstore (or object store, or key-value store) that you can share with the world. It can store any amount up to terabytes of data. In addition, since GCE has Internet connectivity, you can connect to any storage resources located anywhere.</p><p>GCE lets you create a persistent disk from a stored disk image, and you can add persistent disks to and remove them from a running VM. You can launch a VM from a persistent root disk. You can also take snapshots of existing persistent disks and restore them across zones and regions, which can work well with GCE's ability to attach a single read-only disk to multiple VMs.</p><p>Each VM is isolated, from every other, and Anderson says isolation between workloads is key to GCE's predictable performance. If you use scratch storage, your spindles are dedicated to your use alone. In addition, all data is encrypted at rest. Speaking of security, service accounts give you frictionless OAuth 2.0 access to authenticate from GCE VMs or App Engine apps to other Google APIs.</p><p>And speaking of predictable performance, Anderson says GCE lets you hot-add and hot-remove external IP addresses from running VMs and move them across zones, which can be helpful if a machine with a static IP address starts having problems.</p><p>After outlining all the features of Google Cloud Platform, Anderson offered a demo during which he started 200 VMs via the Quick Start UI, an App Engine app, in a minute and 37 seconds.</p><p><iframe allowfullscreen="" mozallowfullscreen="" src="http://player.vimeo.com/video/64849198" webkitallowfullscreen="" frameborder="0" height="300" width="400"></iframe></p><p>He also noted that when <a href="http://www.mapr.com/resources/videos/mapr-terasort-record" target="_blank">MapR broke the Terasort benchmark record</a> last year, it did so by spinning up a thousand four-core GCE VMs, which it could do in a matter of minutes. By contrast, the old record-holder took months to build a dedicated cluster to run the benchmark.</p><h3>Cloud Storage</h3><p>Cloud Storage complements the Compute component of the Google Cloud Platform, and serves as the glue between all Google Cloud Services. Cloud Storage is an HTTP service that serves data directly over HTTP. It has strong read-after-write consistency - no waiting for the data to be replicated. It offers streaming uploads and resumable transfers of objects up to terabytes in size. It serves static data directly via HTTP. It supports two APIs - the same JSON and OAuth 2.0 API GCE uses, and a second that's compatible with other cloud storage providers such as Eucalyptus and AWS S3 that use XML. Cloud Storage also lets you use signed URLs to delegate access to storage to non-authenticated users.</p><p>Behind the scenes, Google replicates Cloud Storage to data centers spanning multiple geographically diverse locations, and makes it accessible via Google's worldwide network. All hardware is fault-tolerant, and the platform itself can scale up or down to meet varying needs.</p><h3>Get a Fast Track to Google Compute Engine</h3><p>GCE generated a lot of interest at RightScale Compute - Anderson's session was standing room only. If you're a RightScale customer, GCE is available to you today. To take advantage of&nbsp; RightScale dynamic configuration to fully automate provisioning, operations, and disaster recovery on GCE so you can focus on developing your applications, <a href="https://www.rightscale.com/free-trial?utm_source=Unified%20Free%20Trial&amp;utm_medium=blog&amp;utm_campaign=An%20Introduction%20to%20the%20Google%20Cloud%20Platform%20from%20an%20Insider" target="_blank">sign up for a RightScale free trial</a>.</p> </div></div></div>Fri, 10 May 2013 20:58:33 +0000Lee Schlesinger260 at http://www.rightscale.com/bloghttp://www.rightscale.com/blog/cloud-industry-insights/introduction-google-cloud-platform-insider#commentsGoogle Compute Engine & RightScale to Sell High-Performance Cloudhttp://www.rightscale.com/blog/rightscale-news/google-compute-engine-rightscale-sell-high-performance-cloud
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</div> <!-- /.easy_social_box --><div class="field field-name-body field-type-text-with-summary field-label-hidden"><div class="field-items"><div class="field-item even" property="content:encoded"> <p>Last week we <a href="http://www.rightscale.com/news_events/press_releases/2013/rightscale-first-to-resell-google-compute-engine.php" target="_blank">announced</a> that RightScale has become Google's first partner to resell <a href="http://www.rightscale.com/products-and-services/multi-cloud-platform/google-cloud-management" target="_blank">Google Compute Engine</a>. This news marks a milestone in a long and ongoing process. We have been working with Google on Google Compute Engine since 2011, providing input on its development and integrating RightScale — and that work just won us Google's North American Partner of the Year for Cloud Platform award. We were at Google I/O last year for the launch of Google Compute Engine, and we've been impressed with the platform's power, building as it does on Google’s expertise at running global scale infrastructure. Although it is still in technical preview, we think Google Compute Engine is going to be a strong competitor in the public IaaS space, and RightScale can help customers get on board now.</p><p>With RightScale, customers will not only <a href="http://www.rightscale.com/products-and-services/multi-cloud-platform/google-cloud-management" target="_blank">get a fast onramp to Google Compute Engine</a>, but will also benefit from our seven-plus years of experience with cloud, our intimate knowledge of all the clouds we support, and the highest level of support to ensure that their projects are successful. The first step in cloud computing is using the right infrastructure for the right purpose, and that's our expertise.</p><p>That’s been the experience of GuruMenu, a company that helps retail brands connect with consumers in real time on mobile devices. The company turned to RightScale to manage the onboarding and deployment of its location-based content on proprietary in- and out-of-store marketing platforms via Google Compute Engine, and to accelerate time-to-market for its new application and provide ongoing management capabilities such as auto-scaling, automation, and monitoring.</p><div style="width: 317px;float:right;"><a href="/sites/default/files/2013/03/img_9777-small_0.jpg"><img alt="Google" class="media-image size-full wp-image-2530" height="461" style="" width="307" typeof="foaf:Image" src="http://www.rightscale.com/blog/sites/default/files/styles/large/public/2013/03/img_9777-small_0.jpg?itok=KMb6qm4A" /></a> RightScale was named Google's North American Partner of the Year for Cloud Platform<p>&nbsp;</p></div><p>With the partnership between RightScale and Google Compute Engine, customers now have yet another cloud provider to choose from as part of our integrated ecosystem of clouds, software vendors, and systems integrators. Our customers benefit from this ecosystem by being able to implement the solutions that best support their business requirements for service level, geography, security, compliance, and performance. Given that there are more cloud options today than ever, businesses shouldn’t have to lock themselves into a single provider. By using RightScale, companies get a unified environment to facilitate management of their applications across public, private, and hybrid infrastructure, which enables them to fully realize the cost and agility benefits of cloud.</p><p>We're continuing to work with Google on a number of initiatives, many of which are in development now. But today's announcement says we're open for business, which is when cloud gets fun — real solutions, use cases, and workloads coming to life. Our goal is to provide you with the ability to use any and all cloud providers you choose and to easily manage your applications among them, and our support for Google Compute Engine is a big milestone on that path. If you're considering Google Compute Engine, see how <a href="http://www.rightscale.com/contact?utm_source=Contact%20Us&amp;utm_medium=blog&amp;utm_campaign=Google%20Compute%20Engine%20%26%20RightScale%20to%20Sell%20High-Performance%20Cloud" target="_blank">RightScale can help you get started</a>.</p> </div></div></div>Mon, 04 Mar 2013 20:33:34 +0000Bailey Caldwell211 at http://www.rightscale.com/bloghttp://www.rightscale.com/blog/rightscale-news/google-compute-engine-rightscale-sell-high-performance-cloud#commentsHow to Manage Cloud Costs and Optimize Resource Usagehttp://www.rightscale.com/blog/cloud-cost-analysis/how-manage-cloud-costs-and-optimize-resource-usage
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</div> <!-- /.easy_social_box --><div class="field field-name-body field-type-text-with-summary field-label-hidden"><div class="field-items"><div class="field-item even" property="content:encoded"> <p>Last year RightScale announced the <a href="http://www.rightscale.com/blog/2012/07/18/forecast-cloud-costs-with-planforcloud/" target="_blank" title="acquisition of PlanForCloud">acquisition of PlanForCloud</a>, a cloud cost forecasting tool that enables you to model your cloud infrastructure, run it through a simulation, and get a three-year cost report showing what your deployment will cost. We know how hard it can be to figure out cloud costs and optimize your usage, so we made it easier with our <a href="http://www.planforcloud.com/" target="_blank" title="free cloud cost forecasting tool">free cloud cost forecasting tool</a>.</p><p>We’ve since added a number of new features, which I’ll highlight here. Plus I’ve got some tips on how you can use this powerful tool to plan and budget for your cloud costs.</p><p><!--more--><b id="internal-source-marker_0.9945264705456793">1. Filter Your Cloud Resource Options by CPU Count and RAM</b></p><p>When it comes to choosing cloud resources, you have many different options from various cloud providers. Resources fall into three broad categories: <a href="http://www.planforcloud.com/pages/resources/cloud_services.html" target="_blank" title="servers, storage, and databases">servers, storage, and databases</a>. To make it easy for you to compare and choose the right resources for your needs, you can filter using the CPU count and RAM that your application requires and compare different resources, as shown in this example:</p><div style="width: 650px;"><a href="/blog/sites/default/files/2013/01/screen-shot-2013-01-07-at-23-11-20.png"><img alt="PlanForCloud server cost comparison" class="wp-image-2105 " src="/blog/sites/default/files/2013/01/screen-shot-2013-01-07-at-23-11-20.png?w=640" style="width: 640px; height: 292px;"></a> <em>When comparing the costs of various cloud infrastructure providers, you have the option to filer by CPU count and RAM.</em><p><b id="internal-source-marker_0.9945264705456793" style="line-height: 1.538em;">2. Get the Full Picture of Your Requirements, Not Just Your Servers</b><span style="line-height: 1.538em;"> </span></p><p><span style="line-height: 1.538em;">We have talked to many users who began using the cloud with the assumption that hourly server costs were all they needed to consider. But when they got their bills, they were shocked to discover that there were many other costs that they had not taken into account. With PlanForCloud, you can avoid being unpleasantly surprised by modeling all the major components of your deployments including:</span></p></div><ul><li>Server running hours</li><li>Storage costs</li><li>Snapshot costs</li><li>Read and write request costs</li><li>Archiving costs</li><li>Database running costs</li><li>Database transaction costs (IO)</li><li>Data transfer costs (including within a deployment and outside of a deployment)<br>&nbsp;</li></ul><div style="width: 650px;"><a href="/blog/sites/default/files/2013/01/screen-shot-2013-01-07-at-23-14-27.png"><img alt="PlanForCloud three-yearcloud cost report" class="size-large wp-image-2106" src="/blog/sites/default/files/2013/01/screen-shot-2013-01-07-at-23-14-27.png?w=640" style="width: 640px; height: 465px;" title="PlanForCloud three-year cloud cost report"></a> <em>The PlanForCloud three-year cost report breaks down your cloud deployment costs per month.</em><p><b id="internal-source-marker_0.9945264705456793" style="line-height: 1.538em;">3. Compare Purchase Options and Clouds </b></p><p><span style="line-height: 1.538em;">PlanForCloud includes prices for AWS, Rackspace, Google Compute Engine, Windows Azure, and SoftLayer. Many of our users are attempting to determine if they should buy AWS reserved instances rather than on-demand instances and, if so, whether those reserved instances need to accommodate light, medium or heavy utilization. When it comes to larger reserved instance purchases, you need to look at the upfront purchase costs versus lower monthly costs. To preserve cash flow, many larger consumers choose to stagger their reserved instance purchases to better cope with the upfront purchase costs.</span></p></div><div style="width: 650px;"><a href="/blog/sites/default/files/2013/01/screen-shot-2013-01-07-at-23-18-06.png"><img alt="PlanForCloud cost breakdown for AWS" class="wp-image-2107" src="/blog/sites/default/files/2013/01/screen-shot-2013-01-07-at-23-18-06.png?w=640" style="width: 640px; height: 253px;" title="PlanForCloud cost breakdown for AWS"></a> <em>This PlanForCloud cost report shows pricing options for AWS, including the cost of on-demand vs. reserved instances.</em><p><b id="internal-source-marker_0.9945264705456793" style="line-height: 1.538em;">4. Forecast How Much Your Growth Will Cost</b><span style="line-height: 1.538em;"> </span></p><p>One of the main benefits of the cloud is the ability to increase your cloud usage and grow. However, this growth comes at a price. With PlanForCloud, you can use <a href="http://www.planforcloud.com/pages/docs/patterns.html" target="_blank" title="growth patterns">growth patterns</a> to model your growth to see how much it will cost. There are two types of growth you can model:</p></div><ul><li><strong>Temporary Growth:</strong> A temporary growth pattern is one in which you see a peak in usage, but after the peak is over, your usage comes back down to normal. Many of our users prefer temporary patterns to forecast their costs for occasions when they issue press releases or launch marketing campaigns, to prepare for seasonality-influenced traffic spikes, or to design one-time experimental loads hitting their applications.</li><li><strong>Permanent Growth:</strong> A permanent growth pattern occurs when your usage of the cloud is constantly increasing. For example, as your user count grows, your app servers increase, and your storage and database requirements also grow.</li></ul><p>You can always use a mix of both temporary and permanent patterns to model your growth requirements. In the example below, we are doing what-if analysis for MySQL/Amazon RDS based on hypothetical database requirements:</p><div style="width: 650px;"><a href="/blog/sites/default/files/2013/01/screen-shot-2013-01-07-at-23-19-36.png"><img alt="Using PlanForCloud to model growth patterns for cloud resource usage" class="wp-image-2108 " src="/blog/sites/default/files/2013/01/screen-shot-2013-01-07-at-23-19-36.png?w=640" style="width: 640px; height: 271px;" title="Using PlanForCloud to model growth patterns for cloud resource usage"></a> <em>PlanForCloud growth modeling provides comparative costs for such resources as application servers, storage, and databases.</em><p>&nbsp;</p></div><p><b id="internal-source-marker_0.9945264705456793">5. Import a Snapshot of Your Cloud Deployments Into PlanForCloud</b></p><p>Many of our users already have proof-of-concept projects or applications running in the cloud. We have added the ability to import your existing cloud resources into PlanForCloud to forecast your costs and compare your options. This feature is currently enabled for AWS only. However, we will soon offer the capability for you to import cloud resources from other cloud providers as well as from RightScale.<br><a href="/blog/sites/default/files/2013/01/screen-shot-2013-01-07-at-23-20-55.png"><img alt="Import from AWS and forecast future costs" class="alignnone size-large wp-image-2109" src="/blog/sites/default/files/2013/01/screen-shot-2013-01-07-at-23-20-55.png?w=640" style="width: 640px; height: 303px;"></a><br>To use these new features to help you better understand and forecast your cloud costs, simply <a href="https://planforcloud.rightscale.com/users/sign_up" target="_blank" title="sign up to use PlanForCloud (it's free)">sign up to use PlanForCloud (it's free)</a> or <a href="https://planforcloud.rightscale.com/deployments?ga=guest_login" target="_blank" title="log in as a guest">log in as a guest</a>.</p><p>And to keep up to date with all the latest on PlanForCloud news and features, follow us on Twitter <a href="https://twitter.com/PlanForCloud" target="_blank" title="@PlanForCloud">@PlanForCloud</a>. We would also love to hear your feedback and feature suggestions via our <a href="https://planforcloud.uservoice.com/forums/142441-planforcloud-feedback" target="_blank" title="PlanForCloud feedback portal">PlanForCloud feedback portal</a>.</p> </div></div></div>Tue, 08 Jan 2013 23:34:14 +0000Hassan Hosseini153 at http://www.rightscale.com/bloghttp://www.rightscale.com/blog/cloud-cost-analysis/how-manage-cloud-costs-and-optimize-resource-usage#commentsRightScale Joins Google Compute Engine for Launch Dayhttp://www.rightscale.com/blog/cloud-industry-insights/rightscale-joins-google-compute-engine-launch-day
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</div> <!-- /.easy_social_box --><div class="field field-name-body field-type-text-with-summary field-label-hidden"><div class="field-items"><div class="field-item even" property="content:encoded"> <p>Today we'll be demoing RightScale managing a <a href="http://www.rightscale.com/products-and-services/multi-cloud-platform/google-cloud-management" target="_blank">deployment on Google Compute Engine</a> during the launch presentation at Google I/O at 1:30pm (PT). With the release of Google Compute Engine, the year 2012 is becoming a turning point in the evolution of cloud computing. There are now multiple public megaclouds on the market, and public cloud computing is set to become the dominant form of business computing (mobile arguably becoming the dominant form of consumer computing). I'll come back to why I am convinced of this at the end, but first let's focus on Google Compute Engine.</p><p>We've been working for months with the team at Google building out Google Compute Engine to ensure that everything is ready for our customers to leverage it. We realized very quickly that Google Compute Engine is an all-out effort to b<a href="/sites/default/files/2012/06/fireshot-1.png"><img alt="Google Compute Engine in the RightScale Dashboard" class="alignright size-medium wp-image-1553" src="/blog/sites/default/files/2012/06/fireshot-1.png?w=300" style="width: 300px; height: 101px; float: right; padding-left: 10px;" title="Google Compute Engine in the RightScale Dashboard"></a>uild a world-class cloud on one of the most awesome global computing infrastructures. It also became clear that Google Compute Engine is comparable to the most successful infrastructure clouds in the market but not a clone in any way. The team at Google has leveraged the depths of Google's engineering treasure trove to bring us their take on how a cloud platform ought to look. Yes, this means that Google Compute Engine is not API compatible with any other cloud. Yes, it also means that resources in Google Compute Engine behave slightly differently from other clouds. However, to RightScale users this will not be an obstacle as our platform takes care of the API differences and our <a href="http://blog.rightscale.com/2010/03/22/rightscale-servertemplates-explained/" target="_blank" title="ServerTemplates">ServerTemplates</a> accept and even leverage the more important resource differences. We actually welcome these differences.</p><p>Each time I gave feedback to the Google Compute Engine team I had to think whether if, by asking them to make it look more like another cloud, I was asking for something better in the long term or whether I was just trying to shave off a couple of hours from our implementation task at the expense of stifling innovation. Given how nascent cloud computing still is in the big picture, the last thing we need is to cut off innovation for standardization.</p><p>How does Google Compute Engine look? Familiar yet different. You get state-of-the-art machine instances with 1, 2, 4, or 8 cores, 3.75GB of memory per core, and optionally 1-2 local "ephemeral" disks. You can create private networks for your instances, attach public IP addresses via 1-1 NAT, and define firewall rules for ingress. You can further attach persistent network disks up to 1TB in size that will have snapshot backup capability very soon. All this is presented through a very clean REST API. Machine images can be constructed from scratch to produce clean never-booted images, uploaded to Google Cloud Storage and registered with Google Compute Engine.</p><p>Overall, Google Compute Engine has been a pleasure to work with, which is perhaps best summed up by RightScale customer Joe Emison who says, "[we]&nbsp;have found the performance of the Google Compute Engine VMs to be the most consistent of any other virtualized architecture we’ve used." Joe is VP of Research and Development at <a href="http://www.buildfax.com/public/about/index.html" target="_blank" title="BuildFax">BuildFax</a> and a long-time RightScale customer who helped us test drive Google Compute Engine. We now look forward to onboarding many more customers, and invite you to sign up for the <a href="http://www.rightscale.com/contact?utm_source=Contact%20Us&amp;utm_medium=blog&amp;utm_campaign=RightScale%20Joins%20Google%20Compute%20Engine%20for%20Launch%20Day" target="_blank" title="Google Compute Engine with RightScale private beta">Google Compute Engine with RightScale private beta</a>.</p><p><iframe allowfullscreen="" mozallowfullscreen="" src="http://player.vimeo.com/video/44739599" webkitallowfullscreen="" frameborder="0" height="300" width="400"></iframe></p><p>One very aggressive innovation that Google Compute Engine brings to cloud computing is encryption of data at rest, both for local ephemeral drives as well as for network attached drives. In the case of the network attached disks the encryption happens on the host before it is put on the network, so it's also encrypted in transit. The encryption is on a per-project basis (Google's term for an account). This is a big deal for security conscious organizations, especially those having regulatory or other mandates to encrypt all data at rest. On other clouds one solution is to run a loop-back crypto driver, but that eats into the VM's performance. I've been benchmarking the Google Compute Engine disk performance (more on that in a future post) and the encryption doesn't seem to have a noticeable impact on performance. Pretty awesome.</p><p>Another interesting feature that highlights Google's worldwide infrastructure is the fact that the private networks to which instances attach are global. This means that as Google Compute Engine's footprint stretches around the globe, customers can create private networks that connect their instances globally. This matters when you operate sites in multiple geographies and when operating disaster recovery deployments. Specifically, it makes it easier to replicate data using the private connectivity as opposed to having to traverse the public internet. Also, it makes it easier for all servers globally to connect to central resources, such as for configuration or distribution of assets. The network traffic is not encrypted, so I would still use an SSL or SSH type of pipe, but it means that the ports used for this traffic can be kept private. And, "by the way," your traffic is carried on Google's worldwide network!</p><p>Being a brand-new offering, Google Compute Engine does have its rough edges. One of them is the fact that for the time being it is subject to maintenance windows on a well-publicized schedule, which I have observed over the last 6 months. This is not a big issue for the large-scale data processing workloads that Google is initially focusing on. In addition, for modern deployment architectures that are built with redundancy and continuous deployment in mind, this can be worked into the process. In fact, it enforces a healthy relaunch of all resources on a continuous schedule. Another rough spot is that disks cannot be mounted while an instance is running, rather only at boot time. That makes it more difficult to manage backup and restore or to have the server self-mount the appropriate snapshots. Both issues are on the "fix as soon as possible" list at Google, so we look forward to improvements.</p><p>In the big picture, the most significant and perhaps most profound reason for Google Compute Engine's existence is the synergy with other Google cloud services. Currently Google offers Cloud Storage, Big Query, App Engine, and Cloud SQL as independent services. But if you look under the covers of App Engine there are services for message queues, push channels to browsers and mobile devices,&nbsp; NoSQL data stores, email, and more. All this starts to add up to as impressive a portfolio of cloud services as anyone can offer and up until today it was missing just one thing: a compute engine to tie it all together.</p><p>Coming back to the turning point in public cloud computing, it seems clear to me that public clouds will be front and center in the future of computing as a whole. It's not even a cost argument. It's an innovation argument. The public cloud environment is not about a virtual machine. It's about a virtually unlimited scale of machines. It's about a growing portfolio of cloud services from storage, to database, to communication, to queuing, and more. Do you really want to or need to run your own replicated, redundant, scalable SQL or NoSQL data store yourself? It's also about location and connectivity: Run anywhere and connect to everything. I'm not claiming that there is no place for private clouds, but that the innovation at almost all levels of computing will happen in public clouds first and from there may trickle down to private cloud environments. Strap in your seats, the public cloud rocket is on the launch pad!</p> </div></div></div>Thu, 28 Jun 2012 18:00:20 +0000Thorsten von Eicken134 at http://www.rightscale.com/bloghttp://www.rightscale.com/blog/cloud-industry-insights/rightscale-joins-google-compute-engine-launch-day#comments